Build the Takens vectors

load("data/data1.rda")

t <- nrow(data1)
f <- ncol(data1)
g <- as_tibble(data1) %>%
  gather() %>%
  mutate(key = rep((1:f), each = t)) %>%
  mutate(Time = rep(1:t, f))
colnames(g) <- c("Cable", "Value", "Time")
p1 <- ggplot(g, aes(x = Time, y = Cable, fill = Value)) +
  geom_tile() +
  scale_fill_gradientn(
    colours = c("#F0E442", "#000000", "#000000"),
    values = c(0, 0.1, max(data1))
  ) +
  ylab("Time Series ID") +
  scale_y_continuous(breaks = seq(0, 600, 100)) +
  scale_x_continuous(breaks = seq(0, 1400, 200)) +
  xlab("Time") +
  theme(legend.position = "none", axis.title = element_text(size = 15))
print(p1)

## This loop builds the Takens' vectors for a given collection of time series
ts <- as.ts(data1[1,])
takens<-nonlinearTseries::buildTakens(ts, 3, 1)
plot(takens)

plotdata<- as_tibble(takens)
p <- plot_ly(plotdata, x = ~V1, y = ~V2, z = ~V3, size = I(3)) %>%
  layout(title = "3D Scatter plot")
p

## No trace type specified:
##   Based on info supplied, a 'scatter3d' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter3d

## No scatter3d mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode